Knowledge Hut

NOVEMBER 17, 2023

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. is the responsibility of data engineers.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Rockset

OCTOBER 11, 2022

Introduction Managing streaming data from a source system, like PostgreSQL, MongoDB or DynamoDB, into a downstream system for real-time analytics is a challenge for many teams. Logstash is an event processing pipeline that ingests and transforms data before sending it to Elasticsearch.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Edureka

FEBRUARY 9, 2023

The most common data storage methods are relational and non-relational databases. Understanding the database and its structures requires knowledge of SQL. Data is moved from databases and other systems into a single hub, such as a data warehouse, using ETL (extract, transform, and load) techniques.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 19, 2022

Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Relational and non-relational databases are among the most common data storage methods. Learning SQL is essential to comprehend the database and its structures. The final step is to publish your work.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

OCTOBER 8, 2021

They are applied to retrieve data from the source systems, perform transformations when necessary, and load it into a target system ( data mart , data warehouse, or data lake). So, why is data integration such a big deal? Connections to both data warehouses and data lakes are possible in any case.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52